Results 101 to 110 of about 584,753 (230)

The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy

Frontiers in Neurology, 2019
Brain functions do not arise from isolated brain regions, but from interactions in widespread networks necessary for both normal and pathological conditions.
Elhum A. Shamshiri, Laurent Sheybani, Serge Vulliemoz, Serge Vulliemoz   +3 more
doaj   +1 more source

Improving Adult Vision Through Pathway‐Specific Training in Augmented Reality

Advanced Science, EarlyView.
Traditional perceptual training approaches are limited by stimulus specificity, treatment efficacy, and patient compliance. A novel altered reality (AR) method is developed to enhance pathway‐specific functions in human adults while performing everyday activities.
Yige Gao, Yulian Zhou, Qing He, Wen Wen, Peng Zhang   +4 more
wiley   +1 more source

Cholinergic agonist-antagonist interactions on neocortical and limbic EEG activation [PDF]

, 1967
Yamamoto Kjen-Ichi, Edward F. Domino
openalex   +1 more source

Microglial MS4A4A Protects against Epileptic Seizures in Alzheimer's Disease

Advanced Science, EarlyView.
This study has unveiled significant new insights into the role of MS4A4A in Alzheimer's disease‐related epilepsy, highlighting its impact on microglial phagocytosis, mitochondrial metabolism, and cytoskeleton, and demonstrating its therapeutic potential in epilepsy management.
Meng Jiang, Qingqing Li, Jianhui Chen, Ruochong Li, Jun Yao, Yong Hu, Haizheng Zhang, Lixin Cai, Maoguo Luo, Yu Sun, Wenwen Zeng   +10 more
wiley   +1 more source

A Dual‐Modal Wearable Pulse Detection System Integrated with Deep Learning for High‐Accuracy and Low‐Power Sleep Apnea Monitoring

Advanced Science, EarlyView.
A dual‐modal wearable pulse detection system is developed for sleep apnea monitoring by integrating a self‐powered PENG and PPG sensor with a biomimetic fingertip structure. Through a two‐stage detection strategy, continuous PPW monitoring and on‐demand PPG detection achieve high‐accuracy sleep apnea recognition while maintaining low power consumption.
Jia Wang, Jiangtao Xue, Yang Zou, Yuxin Ma, Junhan Xu, Yanming Li, Fei Deng, Yiqian Wang, Kai Xing, Zhou Li, Tong Zou   +10 more
wiley   +1 more source

Wireless Technologies for Wearable Electronics: A Review

Advanced Electronic Materials, EarlyView.
This review discusses recent advancements in wireless wearable electronics, focusing on communication technologies and power solutions. It covers key design considerations, explores wireless protocols from short‐ to long‐range networks, and examines powering methods such as integrated sources and energy harvesting.
Choong Yeon Kim, Juhyun Lee, Eun Young Jeong, Yeji Jang, Heesoo Kim, Bohyung Choi, Donggi Han, Youngjun Oh, Jae‐Woong Jeong   +8 more
wiley   +1 more source

Physical Reservoir Computing for Real‐Time Electrocardiogram Arrhythmia Detection Through Controlled Ion Dynamics in Electrochemical Random‐Access Memory

Advanced Electronic Materials, EarlyView.
This study presents an ECRAM‐based physical reservoir computing system for real‐time electrocardiogram arrhythmia detection. By optimizing electrolyte ionic conductivity and channel ionic diffusivity, it achieves including non‐linear dynamics, millisecond‐scale tunable retention, low‐power operation, and minimal variation.
Kyumin Lee, Dongmin Kim, Jongseon Seo, Hyunsang Hwang   +3 more
wiley   +1 more source

Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identification

, 2017
In this article we present the results of our research related to the study of correlations between specific visual stimulation and the elicited brain's electro-physiological response collected by EEG sensors from a group of participants. We will look at
Omelianenko, Iaroslav
core  

Psychometric study of children with learning problems and 14-6 positive spike EEG patterns, treated with ethosuximide (Zarontin) and placebo. [PDF]

, 1968
W. Lynn Smith, M. J. Philippus, H. L. Guard   +2 more
openalex   +1 more source

Contactless Triboelectric Sensing for Real‐Time 3D Motion Recognition in Human‐Computer Interaction

Advanced Electronic Materials, EarlyView.
In the era of artificial intelligence and Internet of Things, there is an increasing demand for intuitive and efficient human‐computer interaction (HCI) technologies. This study presents a contactless triboelectric detector‐based HCI system for classifying 3D motion patterns with 99.33% accuracy.
Qinghao Xu, Junhao Gong, Jiayi Chen, Yimeng Zhang, Hongfa Zhao, Jiaqi Yin, Runze Zhao, Chuqiao Lyu, Wenbo Ding, Changsheng Wu   +9 more
wiley   +1 more source